Contribution Of Artificial Intelligence Research Articles

AI for Climate Action: Leveraging Artificial Intelligence to Address Climate Change Challenges

This comprehensive article explores the transformative role of Artificial Intelligence (AI) in addressing the global climate crisis, focusing on its applications in climate modeling, renewable energy optimization, and disaster response. Through an extensive literature review, case studies, and expert interviews, we examine how AI technologies are revolutionizing climate prediction accuracy, enhancing data processing capabilities, and enabling sophisticated climate scenario simulations. The article delves into AI's contributions to renewable energy forecasting, smart grid management, and energy storage optimization, highlighting its potential to accelerate the transition to sustainable energy systems. We also investigate AI-driven approaches to disaster response and resilience, including early warning systems, resource allocation during climate-related disasters, and post-disaster recovery planning. While acknowledging the significant advancements AI brings to climate action, this study also addresses the challenges and limitations, such as data quality issues, ethical considerations, and technical barriers. Looking ahead, we discuss emerging AI technologies, their integration with other solutions, and the policy implications for effective climate change mitigation and adaptation. This research underscores the critical role of AI in combating climate change, while emphasizing the need for responsible development and deployment of these technologies to ensure a sustainable and resilient future.

Artificial intelligence for enhancing resilience

In an increasingly complex and unpredictable world, resilience-the ability to withstand and recover from adverse conditions is essential across various sectors. This research paper investigates the transformative potential of artificial intelligence (AI) in enhancing resilience across multiple domains. We explore how AI technology can be utilized to develop resilient infrastructure, providing advanced predictive maintenance and real-time monitoring capabilities that ensure robustness and longevity. The study examines the role of AI in improving disaster response, offering rapid data analysis and decision-making support to enhance emergency management outcomes. In climate change, AI-driven strategies are assessed for their effectiveness in fostering climate resilience, including predictive modeling of extreme weather events and optimizing resource allocation. The paper also discusses AI applications in healthcare resilience, such as enhancing diagnostics, patient care, and operational efficiency during crises. Business continuity and crisis management are examined, highlighting AI's capability to anticipate disruptions and maintain operational stability. The paper emphasizes the importance of strengthening cybersecurity resilience using AI to detect and mitigate threats proactively. AI's role in enhancing community and social resilience is analysed, particularly in supporting vulnerable populations and fostering social cohesion. Additionally, we explored AI-powered solutions for urban resilience, focusing on smart cities and sustainable development. The study also covers AI's contributions to environmental and ecological resilience, resilient supply chain management, and resilience in the hospitality and tourism industry. Finally, we investigated AI's potential in fostering psychological resilience, providing personalized mental health support and stress management tools. Through these diverse applications, the paper underscores AI's critical role in building a resilient future.

Artificial intelligence in human resource development: An umbrella review protocol.

The recent surge in artificial intelligence (AI) has significantly transformed work dynamics, particularly in human resource development (HRD) and related domains. Scholars, recognizing the significant potential of AI in HRD functions and processes, have contributed to the growing body of literature reviews on AI in HRD and related domains. Despite the valuable insights provided by these individual reviews, the challenge of collectively interpreting them within the HRD domain remains unresolved. This protocol outlines the methodology for an umbrella review aiming to systematically synthesize existing reviews on AI in HRD. The review seeks to address key research questions regarding AI's contributions to HRD functions and processes, as well as the opportunities and threats associated with its implementation by employing a technology-aided systematic approach. The coding framework will be used to synthesize the contents of the selected systematic reviews such as their search strategies, data synthesis approaches, and HRD-related findings. The results of this umbrella review are expected to provide insights for HRD scholars and practitioners, promoting continuous improvement in AI-driven HRD initiatives. This protocol is preregistered on the Open Science Framework (https://doi.org/10.17605/OSF.IO/Z8NM6) on May 27, 2024.

ENHANCING EFFICIENCY WITH ARTIFICIAL INTELLIGENCE IN THE TRANSITION TO A GREEN DIGITAL ECONOMY

This article examines the role of artificial intelligence (AI) in advancing Uzbekistan's green digital economy, following President Shavkat Mirziyoyev's 2021 decree. It highlights AI's contributions to optimizing energy consumption, developing smart infrastructure, and integrating renewable energy. Challenges such as education, infrastructure development, and policy are discussed. Through case studies on Tashkent's smart city projects, solar energy initiatives, and precision farming, the article demonstrates AI's benefits for sustainability and economic growth. The article concludes by emphasizing the significant economic and environmental impacts of AI in Uzbekistan's transition to a green digital economy.

Employee’s Attitude Towards Artificial Intelligence in the Indian Banking Sector

Purpose: This paper aims to examine employees' attitudes towards the utilization of Artificial Intelligence (AI) in the Indian Banking Sector. The study delves into understanding how employees perceive the integration of AI technologies and its impact on various aspects of banking operations.
 
 Theoretical framework: Built upon the significance of AI as a transformative technology, this research seeks insights into employees' perspectives on AI adoption within the Indian Banking Sector. The study is framed within the context of technological implementation and its influence on organizational processes.
 
 Design/Methodology/Approach: Utilizing a mixed-methods approach involving surveys and interviews, this study collects data on employees' attitudes towards AI in banking. A questionnaire captures diverse viewpoints, while interviews provide deeper insights into the reasons underlying these attitudes.
 
 Findings: The study uncovers a range of employee attitudes towards AI integration in the Indian Banking Sector. Positive responses highlight AI's contributions in areas like accounting, sales, contracts, and cybersecurity. Conversely, some employees express concerns about job security and advocate for enhanced training and upskilling opportunities.
 
 Research, Practical & Social implications: This research adds a unique perspective by presenting Indian banking employees' viewpoints on AI implementation. The findings hold practical implications for banking organizations aiming to effectively manage the incorporation of AI technologies while addressing employee concerns. Additionally, the study underscores the importance of facilitating adequate training to ensure a seamless transition.
 
 Originality/Value: This study stands out as one of the limited research endeavors focused on Indian banking employees' attitudes towards AI. By concentrating on this aspect, the research offers valuable insights into the human dimension of technological advancement, contributing both academically and practically to the banking sector.

Concerns About Co-Authoring AI Tools in Academic Papers

Dear Editors With great attention and interest, I read the editors’ short brief yet thought-provoking editorials [1,2] and it has helped me combine valuable information with my research and experiences. Today, artificial intelligence has become an application that we can use in all areas of our lives, being versatile, and able to analyze, collect and interpret. Writing ChatGPT that we can barely bring together for weeks or even months of work, and other AI applications can be used in minutes or even. We seconds can see that it produces original writings and offers a wide range of information. It is obvious that the time-saving experience provided by artificial intelligence provides convenience in most areas of our lives. But that's human researchers and artificial intelligence it may cause us to not understand some points about certain differences between the two. For example, when we look at the difference between an article written with artificial intelligence and an article written with human intelligence, it is undoubtedly almost understandable at first glance impossible. Because of life's developing and changing conditions, no field wanted to be left behind and turned to itself to build its essence, one of which is undoubtedly artificial Intelligence. With the rapid progression of the COVID-19 pandemic and swiftly evolving political decisions, technology has become exceedingly practical and adaptive, undergoing continuous transformation. Many research studies have begun to be conducted around the world, with the need for individuals to conduct faster and more extensive research to bring together new and diverse resources. While the utilization of artificial intelligence (AI) appears as one of the most promising options for this purpose, we must inquire whether its inclusion as a co-author adheres to ethical and technical standards or if it occasionally neglects these principles. In my opinion, involving AI tools like ChatGPT as a co-author can potentially lead to ethical complexities, especially in terms of responsibility and accountability. Language models powered by artificial intelligence lack consciousness, autonomy, and the ability to claim ownership of their contributions. Ascribing authorship to these models blurs lines of responsibility and weakens the ethical obligations inherent in scholarly authorship. Simultaneously, the essence of scholarly authorship lies in the generation of hypotheses, experimentation, data analysis, and interpretation, attributes ascribed to individuals who actively contribute. In this context, even though ChatGPT and other artificial intelligence models expeditiously furnish us with desired information through rapid interactions, it is fundamentally derived from existing human input sources. In essence, these AI systems do not so much transform or recreate a wellspring of knowledge as they present it in its preexisting state. Introducing ChatGPT as a co-author could evoke the assumption of its active engagement, potentially blurring the distinction between the assistance offered by researchers and that by the AI, rendering it challenging for observers to distinctly discern their respective contributions. Consequently, artificial intelligence's contributions, evident when examining scientific articles and many other sources we seek, are undeniably substantial. While the knowledge it presents may introduce entirely novel perspectives, rather than accrediting artificial intelligence as an author, we should confine its recognition to the acknowledgment section solely for its contributions. This approach allows us to acknowledge the collaborative efforts of both human and artificial intelligence, upholding transparency while respecting and adhering to traditional authorship norms. Yours sincerely,

Operational Risk Management: Artificial Intelligence's Contributions to Business Excellence

Operational Risk Management: Artificial Intelligence's Contributions to Business Excellence

Mobile-Phone Based Chemical Analysis - Instrumental Innovations and Smartphone Apps

Main trends in development of analytical instrumentation involve design a measuring instruments, which are able to provide the largest possible amount of analytical information about analyzed material, but simultaneously also simplification and scaling-down analytical instruments towards a possible use directly by users without specialized training. Both those development trends are associated with another important tendency, which is the elimination of direct human effort in carrying out different operations in chemical analytical procedures by design of measuring systems, which are mechanized, robotized, or even completely automated involving various contributions of artificial intelligence. One of elements used also for further instrumental progress, is in recent decade the application of mobile phones in further modification of analytical devices for remote and personal use. The potential utility value of a concept to equip mobile-phones in chemical sensors can be considered as a very efficient way for improving the access to a personal analytical devices for instance in bioanalytical applications, smartphone-based biosensors, and integration of microfluidic devices and smartphones.